Abstract
Appraising some sustainability indicators for changes of others, or comprehensively assessing all metrics, while maintaining sustainability performance, is a crucial consideration for decision-makers. Moreover, numerous real-world applications involve factors that possess an ambiguous status as either input or output, commonly referred to as flexible measures, as well as imprecise measures. Accordingly, this research introduces a fuzzy flexible directional distance model for evaluating sustainable systems with fuzzy flexible measures. Subsequently, a fuzzy inverse directional distance approach, founded on data envelopment analysis and incorporating flexible measures, is proposed to assess the alteration of some imprecise sustainability criteria in response to changes in other measures while maintaining sustainability performance. Also, the modifications of all sustainability dimensions are dealt with while the sustainability performance level remains unchanged. An instance of numerical illustration and practical implementation within the healthcare industry has been presented to showcase the introduced methodology. The findings suggest that the technique proposed in this study has proven to be advantageous and enlightening for evaluating specific dimensions of sustainability in relation to alternations of other indicators or comprehensively addressing modifications of all sustainability indicators, while simultaneously preserving the ability of entities with fuzzy flexible measures.
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References
Amirteimoori A, Emrouznejad A (2011) Flexible measures in production process: a DEA-based approach. RAIRO-Oper Res 45:63–74. https://doi.org/10.1051/ro/2011103
An Q, Liu X, Li Y, Xiong B (2019) Resource planning of Chinese commercial banking systems using two-stage inverse data envelopment analysis with undesirable outputs. PLoS One 14:e0218214–e0218214. https://doi.org/10.1371/journal.pone.0218214
Arana-Jiménez M, Sánchez-Gil MC, Lozano S (2022) A fuzzy DEA slacks-based approach. J Comput Appl Math 404:113180. https://doi.org/10.1016/j.cam.2020.113180
Arya A, Yadav SP (2017) A fuzzy dual sbm model with fuzzy weights: an application to the health sector. In: Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Springer Singapore, pp. 230–238
Ashrafi A, Mansouri M (2019) Generalized fuzzy inverse data envelopment analysis models. Int J Ind Math 11:189–196
Ban A, Brândaş A, Coroianu L, Negruţiu C, Nica O (2011) Approximations of fuzzy numbers by trapezoidal fuzzy numbers preserving the ambiguity and value. Comput Math Appl 61:1379–1401. https://doi.org/10.1016/j.camwa.2011.01.005
Brotons Martínez JM, Sansalvador Selles ME (2015) A fuzzy quality cost estimation method. Fuzzy Sets Syst 266:157–170. https://doi.org/10.1016/j.fss.2014.12.014
Chen L, Wang Y, Lai F, Feng F (2017) An investment analysis for China’s sustainable development based on inverse data envelopment analysis. J Clean Prod 142:1638–1649. https://doi.org/10.1016/j.jclepro.2016.11.129
Cook WD, Zhu J (2007) Classifying inputs and outputs in data envelopment analysis. Eur J Oper Res 180:692–699. https://doi.org/10.1016/j.ejor.2006.03.048
Dotoli M, Epicoco N, Falagario M, Sciancalepore F (2015) A cross-efficiency fuzzy data envelopment analysis technique for performance evaluation of decision making units under uncertainty. Comput Ind Eng 79:103–114. https://doi.org/10.1016/j.cie.2014.10.026
Emrouznejad A, Yang G-l, Amin GR (2019) A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries. J Op Res Soc 70:1079–1090. https://doi.org/10.1080/01605682.2018.1489344
Färe R, Grosskopf S (2010) Directional distance functions and slacks-based measures of efficiency. Eur J Oper Res 200:320–322. https://doi.org/10.1016/j.ejor.2009.01.031
Färe R, Grosskopf S, Lovell CAK, Pasurka C (1989) Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev Econ Stat 71:90–98. https://doi.org/10.2307/1928055
Fukuyama H, Weber WL (2009) A directional slacks-based measure of technical inefficiency. Socioecon Plann Sci 43(4):274–287. https://doi.org/10.1016/j.seps.2008.12.001
Ghobadi S (2018) Inverse DEA using enhanced russell measure in the presence of fuzzy data. Int J Ind Math 10:165–180
Ghobadi S, Jahanshahloo G, Lotfi FH, Rostami-Malkhalifeh M (2014) Dynamic inverse DEA in the presence of fuzzy data. Adv Environ Biol 8:139–151
Hassanzadeh A, Yousefi S, Farzipoor Saen R, Hosseininia SSS (2018) How to assess sustainability of countries via inverse data envelopment analysis? Clean Technol Environ Policy 20:29–40. https://doi.org/10.1007/s10098-017-1450-x
Hatami-Marbini A, Ebrahimnejad A, Lozano S (2017) Fuzzy efficiency measures in data envelopment analysis using lexicographic multiobjective approach. Comput Ind Eng 105:362–376. https://doi.org/10.1016/j.cie.2017.01.009
Jahani Sayyad Noveiri M, Kordrostami S (2021) Sustainability assessment using a fuzzy DEA aggregation approach: a healthcare application. Soft Comput 25:10829–10849. https://doi.org/10.1007/s00500-021-05992-y
Jahani Sayyad Noveiri M, Kordrostami S, Amirteimoori A (2022) Performance analysis of sustainable supply networks with bounded, discrete, and joint factors. Environ Dev Sustain 24:238–270. https://doi.org/10.1007/s10668-021-01415-y
Jorba L, Adillon R (2017) A generalization of trapezoidal fuzzy numbers based on modal interval theory. Symmetry 9:198
Joulaei M, Mirbolouki M, Bagherzadeh-Valami H (2019) Classifying fuzzy flexible measures in data envelopment analysis. J Intell Fuzzy Syst 36:3791–3800. https://doi.org/10.3233/JIFS-18698
Kalantary M, Farzipoor Saen R (2019) Assessing sustainability of supply chains: an inverse network dynamic DEA model. Comput Ind Eng 135:1224–1238. https://doi.org/10.1016/j.cie.2018.11.009
Kalantary M, Farzipoor Saen R, Toloie Eshlaghy A (2018) Sustainability assessment of supply chains by inverse network dynamic data envelopment analysis. Sci Iran 25:3723–3743
Kordrostami S, Jahani Sayyad Noveiri M (2014) Evaluating the performance and classifying the interval data in data envelopment analysis. Int J Manag Sci Eng Manag 9:243–248. https://doi.org/10.1080/17509653.2014.900655
Kordrostami S, Jahani Sayyad Noveiri M (2017) Evaluating the multi-period systems efficiency in the presence of fuzzy data. Fuzzy Inf Eng 9:281–298. https://doi.org/10.1016/j.fiae.2017.09.003
Kordrostami S, Farajpour G, Jahani Sayyad Noveiri M (2014) Evaluating the efficiency and classifying the fuzzy data: a DEA based approach. Int J Ind Math 6:321–327
Kordrostami S, Amirteimoori A, Jahani Sayyad Noveiri M (2016) Ranking of bank branches with undesirable and fuzzy data: a DEA-based approach. Iran J Optim 8:71–77
Kordrostami S, Amirteimoori A, Jahani Sayyad Noveiri M (2019) Inputs and outputs classification in integer-valued data envelopment analysis. Measurement 139:317–325. https://doi.org/10.1016/j.measurement.2019.02.087
Lee KH (2005) Fuzzy number. In: First Course on Fuzzy Theory and Applications. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 129–151. doi:https://doi.org/10.1007/3-540-32366-x_5
Lertworasirikul S, Charnsethikul P, Fang S-C (2011) Inverse data envelopment analysis model to preserve relative efficiency values: the case of variable returns to scale. Comput Ind Eng 61:1017–1023. https://doi.org/10.1016/j.cie.2011.06.014
Lin Y, Yan L, Wang Y-M (2019) Performance evaluation and investment analysis for container port sustainable development in china: an inverse DEA approach. Sustainability 11:4617. https://doi.org/10.3390/su11174617
Orisaremi KK, Chan FT, Chung NS (2021) Potential reductions in global gas flaring for determining the optimal sizing of gas-to-wire (GTW) process: an inverse DEA approach. J Nat Gas Sci Eng 93:103995. https://doi.org/10.1016/j.jngse.2021.103995
Orisaremi KK, Chan FT, Chung SH, Fu X (2022) A sustainable lean production framework based on inverse DEA for mitigating gas flaring. Expert Syst Appl 206:117856. https://doi.org/10.1016/j.eswa.2022.117856
Peykani P, Mohammadi E, Emrouznejad A, Pishvaee MS, Rostamy-Malkhalifeh M (2019) Fuzzy data envelopment analysis: an adjustable approach. Expert Syst Appl 136:439–452. https://doi.org/10.1016/j.eswa.2019.06.039
Puri J, Yadav SP (2014) A fuzzy DEA model with undesirable fuzzy outputs and its application to the banking sector in India. Expert Syst Appl 41:6419–6432
Toloo M (2012) Alternative solutions for classifying inputs and outputs in data envelopment analysis. Comput Math Appl 63:1104–1110. https://doi.org/10.1016/j.camwa.2011.12.016
Toloo M, Allahyar M, Hančlová J (2018) A non-radial directional distance method on classifying inputs and outputs in DEA: application to banking industry. Expert Syst Appl 92:495–506. https://doi.org/10.1016/j.eswa.2017.09.034
Wang Y-M, Chin K-S (2011) Fuzzy data envelopment analysis: a fuzzy expected value approach. Expert Syst Appl 38:11678–11685. https://doi.org/10.1016/j.eswa.2011.03.049
Wegener M, Amin GR (2019) Minimizing greenhouse gas emissions using inverse DEA with an application in oil and gas. Expert Syst Appl 122:369–375. https://doi.org/10.1016/j.eswa.2018.12.058
Wei Q, Zhang J, Zhang X (2000) An inverse DEA model for inputs/outputs estimate. Eur J Oper Res 121:151–163. https://doi.org/10.1016/S0377-2217(99)00007-7
Zhang Q, Gao J (2012) Fuzzy DEA with series network structure. Adv Sci Lett 7(1):600–605. https://doi.org/10.1166/asl.2012.2670
Zhang Yousefi S, Hassanzadeh A, Saen RF, Kashi ZM (2022) Assessing sustainability of Islamic countries via data envelopment analysis (DEA). Clean Technol Environ Policy 24:1129–1143
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MJSN contributed to writing—original draft, methodology, formal analysis, data collection, and software. SK contributed to writing—review and editing, formal analysis, data collection, software, and investigation. All authors read and approved the final manuscript.
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Jahani Sayyad Noveiri, M., Kordrostami, S. Estimating sustainability dimensions using fuzzy inverse directional distance model with flexible measures: a health sector application. Soft Comput 27, 17025–17041 (2023). https://doi.org/10.1007/s00500-023-08666-z
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DOI: https://doi.org/10.1007/s00500-023-08666-z